Abstract
Brain Computer Interface (BCI) systems are the tools that allow the acquisition of biopotential signal spectra, with the most used attention, meditation and eye blinking signals. The main objective of BCI is to translate brain activity in digital form that can be used in different areas such as education, industrial, games, robotics, home automation and medical areas. In particular, this paper focuses on the acquisition and filtering of attention and meditation signals. For this, the variation and behavior of these signals are analyzed against external stimuli and in situations of stress and/or relaxation. EEG signals from the brain were captured by the MindWave Mobile device through the NeuroSky interface at a sampling rate of 1 Hz. The signals obtained are transmitted to two different devices, Arduino (At mega 328) and Raspberry Pi 3 through the Bluetooth module (HC-06) in order to compare the effectiveness of the sending and receiving times. The preliminary results in controlled scenarios allowed us identifying activities where complex mathematical calculations, meditation activities and listening to relaxing music are required. In this same sense, the comparison between the Arduino and Raspberry devices is shown.
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Galíndez-Floréz, I., Coral-Flores, A., Moncayo-Torres, E., Mayorca-Torres, D., Guerrero-Chapal, H. (2020). Biopotential Signals Acquisition from the Brain Through the MindWave Device: Preliminary Results. In: Botto-Tobar, M., Zambrano Vizuete, M., Torres-Carrión, P., Montes León, S., Pizarro Vásquez, G., Durakovic, B. (eds) Applied Technologies. ICAT 2019. Communications in Computer and Information Science, vol 1193. Springer, Cham. https://doi.org/10.1007/978-3-030-42517-3_11
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DOI: https://doi.org/10.1007/978-3-030-42517-3_11
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